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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 613 records · Page 34
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

Dynamic Importance Measures in the ADAPT Framework

Probabilistic Risk Assessment (PRA) uses fault tree/event tree analysis to evaluate the environmental impacts of nuclear power plants due to internal or external initiating events. In a fault tree, basic failure events are assembled using primarily And/Or logic to determine the combinations of failures that lead to failure of the system as a whole. An event tree is forward-facing, and begins with a single initiating event. From there the analysis considers what event may occur next, and branches out among the possible configurations of occurrence and non-occurrence of that event. This branching continues until user-defined end states are reached. End states may include a safe and stable configuration of the plant, or any number of differing failure states. Both fault and event trees require basic event probabilities as inputs to provide insight on the likelihood of different outcomes. PRA has been applied to nuclear power plants as an analysis tool since the 1975 Reactor Safety Study. In a traditional PRA, the order of events is prescribed by the analyst and each event is typically a binary aleatory uncertainty: occurrence or non-occurrence. Discrete dynamic event tree (DDET) analysis eliminates this subjectivity in ordering of events by using the output of a dynamic system model (simulator) to inform the branching. Branching conditions are triggered by the existence of a relevant plant state in the code, and therefore only occur as physically appropriate. The DDET approach also allows consideration of both epistemic and aleatory uncertainties on a phenomenologically and stochastically consistent platform. One current limitation of DDETs is the assessment of results, which is not as well developed as in traditional PRA. A concept that is used in PRA to assess the significance of a basic event is the concept of importance measures (IMs). In traditional PRA, IMs only consider the likelihood of occurrence of non-occurrence of a basic event. The application of importance measures to DDETs must take into consideration not only the occurrence and non-occurrence of an event, but also uncertain timing or severity. This work describes three general dynamic importance measures (DIMs) as implemented in the Analysis of Dynamic Accident Progression Trees (ADAPT) DDET driver code. The measures account for the change in progression of the DDET resulting from the different values of each uncertain variable under investigation. The DIMs are applied to a sample DDET to demonstrate the type of insights that may be gained from each one. These measures will facilitate comparison of the impact of dynamic branching events on a consequence of interest, which also allow DDETs to be used in prioritizing plant investments. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2022

Variability in observed stable water isotopes in snowpack across a mountainous watershed in Colorado

In this study, isotopic information from 81 snowpits was collected over a 5-year period in a large, Colorado watershed. Data spans gradients in elevation, aspect, vegetation, and seasonal climate. They are combined with overlapping campaigns for water isotopes in precipitation and snowmelt, and a land-surface model for detailed estimates of snowfall and climate at sample locations. Snowfall isotopic inputs, describe the majority of δ18O snowpack variability. Aspect is a secondary control, with slightly more enriched conditions on east and north facing slopes. This is attributed to preservation of seasonally enriched snowfall and vapour loss in the early winter. Sublimation, expressed by decreases in snowpack d-excess in comparison to snowfall contributions, increases at low elevation and when seasonal temperature and solar radiation are high. At peak snow accumulation, post-depositional fractionation appears to occur in the top 25 ± 14% of the snowpack due to melt-freeze redistribution of lighter isotopes deeper into the snowpack and vapour loss to the atmosphere during intermittent periods of low relative humidity and high windspeed. Relative depth of fractionation increases when winter daytime temperatures are high and winter precipitation is low. Once isothermal, snowpack isotopic homogenization and enrichment was observed with initial snowmelt isotopically depleted in comparison to snowpack and enriching over time. The rate of δ18O increase (d-excess decrease) in snowmelt was 0.02‰ per day per 100-m elevation loss. Isotopic data suggests elevation dictates snowpack and snowmelt evolution by controlling early snow persistence (or absence), isotopic lapse rates in precipitation and the ratio of energy to snow availability. Hydrologic tracer studies using stable water isotopes in basins of large topographic relief will require adjustment for these elevational controls to properly constrain stream water sourcing from snowmelt.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

High-resolution modeling of indoor radon exposure with uncertainty quantification in Utah

Indoor radon accounts for 37% of population-level exposure to ionizing radiation in the United States. However, radon metrics are typically reported at coarse spatial scales, potentially obscuring meaningful local variation. We developed a high-resolution modeling framework to estimate indoor radon concentrations across Utah while explicitly quantifying predictive uncertainty. A total of 19,497 residential radon measurements collected between 2006 and 2017 were combined with environmental and housing characteristics and analyzed using a geospatial neural network that accommodates spatial dependence and nonlinear associations. Predictions were generated on a uniform hexagonal grid at 0.73 km2 resolution (H3 level 8). Out-of-sample predictions aggregated to the H3 level 8 grid showed good agreement with observed concentrations (Pearson r=0.64), while household-level predictions exhibited more moderate agreement (r=0.45). The model produced well-calibrated uncertainty estimates, with 24.1% of held-out observations exceeding the predicted 75th-percentile threshold. Maps of predicted radon concentrations and the probability of exceeding the U.S. EPA action level of 148 Bq/m3 (4 pCi/L) revealed substantial fine-scale spatial heterogeneity that was not apparent in conventional coarse-resolution summaries, with greater local variability observed in densely monitored urban counties than in sparsely sampled regions. High-resolution radon models that explicitly quantify uncertainty provide a useful framework for characterizing the spatial distribution of indoor radon and identifying areas of elevated exceedance risk. These findings highlight the value of fine-scale monitoring data and uncertainty-aware modeling approaches for radon exposure assessment, environmental risk characterization, and radon-related health research.

Wu, Yunhan [ORNL] (ORCID:0000000178842994)↗
DOE OSTI2015

On the origin of wind line variability in O stars

We analyze 10 UV time series for five stars that fulfill specific sampling and spectral criteria to constrain the origin of large-scale wind structure in O stars. We argue that excited state lines must arise close to the stellar surface and are an excellent diagnostic complement to resonance lines which, due to radiative transfer effects, rarely show variability at low velocity. Consequently, we splice dynamic spectra of the excited state line N iv λ1718 at low velocity with those of Si iv λλ1400 at high velocity in order to examine the temporal evolution of wind line features. These spliced time series reveal that nearly all of the features observed in the time series originate at or very near the stellar surface. Furthermore, we positively identify the observational signature of equatorial corotating interaction regions in two of the five stars and possibly two others. In addition, we see no evidence of features originating further out in the wind. We use our results to confirm the fact that the features seen in dynamic spectra must be huge in order to remain in the line of sight for days, persisting to very large velocity, and that the photospheric footprint of the features must also be quite large, ∼15%–20% of the stellar diameter.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2014

Temporal variability in urinary levels of drinking water disinfection byproducts dichloroacetic acid and trichloroacetic acid among men

Urinary haloacetic acids (HAAs), such as dichloroacetic acid (DCAA) and trichloroacetic acid (TCAA), have been suggested as potential biomarkers of exposure to drinking water disinfection byproducts (DBPs). However, variable exposure to and the short elimination half-lives of these biomarkers can result in considerable variability in urinary measurements, leading to exposure misclassification. Here we examined the variability of DCAA and TCAA levels in the urine among eleven men who provided urine samples on 8 days over 3 months. The urinary concentrations of DCAA and TCAA were measured by gas chromatography coupled with electron capture detection. We calculated the intraclass correlation coefficients (ICCs) to characterize the within-person and between-person variances and computed the sensitivity and specificity to assess how well single or multiple urine collections accurately determined personal 3-month average DCAA and TCAA levels. The within-person variance was much higher than the between-person variance for all three sample types (spot, first morning, and 24-h urine samples) for DCAA (ICC=0.08–0.37) and TCAA (ICC=0.09–0.23), regardless of the sampling interval. A single-spot urinary sample predicted high (top 33%) 3-month average DCAA and TCAA levels with high specificity (0.79 and 0.78, respectively) but relatively low sensitivity (0.47 and 0.50, respectively). Collecting two or three urine samples from each participant improved the classification. The poor reproducibility of the measured urinary DCAA and TCAA concentrations indicate that a single measurement may not accurately reflect individual long-term exposure. Collection of multiple urine samples from one person is an option for reducing exposure classification errors in studies exploring the effects of DBP exposure on reproductive health. - Highlights: • We evaluated the variability of DCAA and TCAA levels in the urine among men. • Urinary DCAA and TCAA levels varied greatly over a 3-month period. • Single measurement may not accurately reflect personal long-term exposure levels. • Collecting multiple samples from one person improved the exposure classification.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

Parameterizing deep convection using the assumed probability density function method

Due to their coarse horizontal resolution, present-day climate models must parameterize deep convection. This paper presents single-column simulations of deep convection using a probability density function (PDF) parameterization. The PDF parameterization predicts the PDF of subgrid variability of turbulence, clouds, and hydrometeors. That variability is interfaced to a prognostic microphysics scheme using a Monte Carlo sampling method.The PDF parameterization is used to simulate tropical deep convection, the transition from shallow to deep convection over land, and mid-latitude deep convection.These parameterized single-column simulations are compared with 3-D reference simulations. The agreement is satisfactory except when the convective forcing is weak. The same PDF parameterization is also used to simulate shallow cumulus and stratocumulus layers. The PDF method is sufficiently general to adequately simulate these five deep, shallow, and stratiform cloud cases with a single equation set. This raises hopes that it may be possible in the future, with further refinements at coarse time step and grid spacing, to parameterize all cloud types in a large-scale model in a unified way.

Storer, R. L.↗
DOE OSTI2020

The frequency of extreme X-ray variability for radio-quiet quasars

ABSTRACT We analyse 1598 serendipitous Chandra X-ray observations of 462 radio-quiet quasars to constrain the frequency of extreme amplitude X-ray variability that is intrinsic to the quasar corona and innermost accretion flow. The quasars in this investigation are all spectroscopically confirmed, optically bright (mi ≤ 20.2), and contain no identifiable broad absorption lines in their optical/ultraviolet spectra. This sample includes quasars spanning z ≈ 0.1–4 and probes X-ray variability on time-scales of up to ≈12 rest-frame years. Variability amplitudes are computed between every epoch of observation for each quasar and are analysed as a function of time-scale and luminosity. The tail-heavy distributions of variability amplitudes at all time-scales indicate that extreme X-ray variations are driven by an additional physical mechanism and not just typical random fluctuations of the coronal emission. Similarly, extreme X-ray variations of low-luminosity quasars seem to be driven by an additional physical mechanism, whereas high-luminosity quasars seem more consistent with random fluctuations. The amplitude at which an X-ray variability event can be considered extreme is quantified for different time-scales and luminosities. Extreme X-ray variations occur more frequently at long time-scales (Δt ≳ 300 d) than at shorter time-scales and in low-luminosity quasars compared to high-luminosity quasars over a similar time-scale. A binomial analysis indicates that extreme intrinsic X-ray variations are rare, with a maximum occurrence rate of $\lt 2.4{{\ \rm per\ cent}}$ of observations. Finally, we present X-ray variability and basic optical emission-line properties of three archival quasars that have been newly discovered to exhibit extreme X-ray variability.

Timlin, III, John D.↗
DOE OSTI2017

Photometric Variability of the Be Star Population

Be stars have generally been characterized by the emission lines in their spectra, and especially the time variability of those spectroscopic features. They are known to also exhibit photometric variability at multiple timescales, but have not been broadly compared and analyzed by that behavior. We have taken advantage of the advent of wide-field, long-baseline, and high-cadence photometric surveys that search for transiting exoplanets to perform a comprehensive analysis of brightness variations among a large number of known Be stars. The photometric data comes from the KELT transit survey, with a typical cadence of 30 minutes, a baseline of up to 10 years, photometric precision of about 1%, and coverage of about 60% of the sky. We analyze KELT light curves of 610 known Be stars in both the northern and southern hemispheres in an effort to study their variability. Consistent with other studies of Be star variability, we find most of the stars to be photometrically variable. We derive lower limits on the fraction of stars in our sample that exhibit features consistent with non-radial pulsations (25%), outbursts (36%), and long-term trends in the circumstellar disk (37%), and show how these are correlated with spectral sub-types. Other types of variability, such as those owing to binarity, are also explored. Simultaneous spectroscopy for some of these systems from the Be Star Spectra database allow us to better understand the physical causes for the observed variability, especially in cases of outbursts and changes in the disk.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

Effective Long-term Monitoring Strategies by Integrating Reactive Transport Models with In situ Geochemical Measurements - 16212

Long-term monitoring of contaminant transport in groundwater is expected to account for a large fraction of future life-cycle cleanup costs at the DOE sites. The Attenuation-Based Remedies in the Subsurface Applied Field Research Initiative (ABRS AFRI) is developing an innovative approach for cost-effective in situ long-term monitoring. The approach is based on strategically adding the measurements of controlling variables (such as pH, redox potential, electrical conductivity, and groundwater level), which control the plume mobility and its spatial and temporal distribution. In situ measurements of these variables - supplemented with a reduced number of standard periodic groundwater samples - are expected to lead to more cost-effective monitoring, and can also serve as an early warning system for detecting unexpected plume migration. The objective of this study is to support the development of such a long-term monitoring approach through the application of advanced computational methods, including (1) statistical data mining and analysis, and (2) three-dimensional flow and reactive chemical transport modeling. We have performed the statistical data analysis of historical and current monitoring data at the Savannah River Site (SRS) F-Area to quantify the correlations between the controlling variables and radioactive contaminant concentrations. In parallel, we have used 3D modeling of flow and contaminant transport to provide the prediction of the contaminant plume evolution. The results of both data analysis and modeling confirmed that the correlations between controlling variables and contaminant concentrations are significant. Modeling results also suggest that the correlation parameters will change in the future, which is important to assess the long-term efficacy of the proposed monitoring approach. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2017

Rapid evaluation of particle properties using inverse SEM simulations

The characteristic X-rays produced by the interactions of the electron beam with the sample in a scanning electron microscope (SEM) are usually captured with a variable-energy detector, a process termed energy dispersive spectrometry (EDS). The purpose of this work is to exploit inverse simulations of SEM-EDS spectra to enable rapid determination of sample properties, particularly elemental composition. This is accomplished using penORNL, a modified version of PENELOPE, and a modified version of the traditional Levenberg Marquardt nonlinear optimization algorithm, which together is referred to as MOZAIK-SEM. The overall conclusion of this work is that MOZAIK-SEM is a promising method for performing inverse analysis of X-ray spectra generated within a SEM. As this methodology exists now, MOZAIK-SEM has been shown to calculate the elemental composition of an unknown sample within a few percent of the actual composition.

Bekar, Kursat B↗
DOE OSTI2016

The most luminous heavily obscured quasars have a high merger fraction: morphological study of wise -selected hot dust-obscured galaxies

Previous studies have shown that Wide-field Infrared Survey Explorer -selected hyperluminous, hot dust-obscured galaxies (Hot DOGs) are powered by highly dust-obscured, possibly Compton-thick active galactic nuclei (AGNs). High obscuration provides us a good chance to study the host morphology of the most luminous AGNs directly. We analyze the host morphology of 18 Hot DOGs at z ∼ 3 using Hubble Space Telescope /WFC3 imaging. We find that Hot DOGs have a high merger fraction (62 ± 14%). By fitting the surface brightness profiles, we find that the distribution of Sérsic indices in our Hot DOG sample peaks around 2, which suggests that most Hot DOGs have transforming morphologies. We also derive the AGN bolometric luminosity (∼10{sup 14} L {sub ⊙}) of our Hot DOG sample by using IR spectral energy distributions decomposition. The derived merger fraction and AGN bolometric luminosity relation is well consistent with the variability-based model prediction. Both the high merger fraction in an IR-luminous AGN sample and relatively low merger fraction in a UV/optical-selected, unobscured AGN sample can be expected in the merger-driven evolutionary model. Finally, we conclude that Hot DOGs are merger-driven and may represent a transit phase during the evolution of massive galaxies, transforming from the dusty starburst-dominated phase to the unobscured QSO phase.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2017

Evaluating the Performance of the IEEE Standard 1366 Method for Identifying Major Event Days

IEEE Standard 1366 offers a method for segmenting reliability performance data to isolate the effects of major events from the underlying year-to-year trends in reliability. Recent analysis by the IEEE Distribution Reliability Working Group (DRWG) has found that reliability performance of some utilities differs from the expectations that helped guide the development of the Standard 1366 method. This paper proposes quantitative metrics to evaluate the performance of the Standard 1366 method in identifying major events and in reducing year-to-year variability in utility reliability. The metrics are applied to a large sample of utility-reported reliability data to assess performance of the method with alternative specifications that have been considered by the DRWG. We find that none of the alternatives perform uniformly 'better' than the current Standard 1366 method. That is, none of the modifications uniformly lowers the year-to-year variability in System Average Interruption Duration Index without major events. Instead, for any given alternative, while it may lower the value of this metric for some utilities, it also increases it for other utilities (sometimes dramatically). Thus, we illustrate some of the trade-offs that must be considered in using the Standard 1366 method and highlight the usefulness of the metrics we have proposed in conducting these evaluations.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2015

Evidence for enhanced persistent emission during sub-eddington thermonuclear bursts

In a recent paper we found evidence for an increase in the accretion rate during photospheric radius expansion bursts, quantified by a variable normalization factor f{sub a} on the preburst persistent emission. Here we follow this result up on a much larger sample of 1759 type I X-ray bursts from 56 sources. We show that the variable persistent flux method provides improvements in the quality of spectral fits for type I bursts, whether or not they reach the Eddington luminosity. The new approach has an estimated Bayes factor of 64 improvement over the standard method, and we recommend that the procedure be adopted as standard for analyzing type I bursts. We show evidence that the remaining discrepancies to a formally consistent spectral model are due to the burst component deviating significantly from a blackbody, rather than variations in the spectral shape of the persistent emission component. In bursts that do not show radius expansion, the persistent emission enhancement does not exceed 37% of the Eddington flux. We use this observation to constrain the Eddington flux of sources for which F{sub Edd} has not been directly measured.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2014

Stochastic modeling of the Fermi/LAT γ-ray blazar variability

We study the γ-ray variability of 13 blazars observed with the Fermi/Large Area Telescope (LAT). These blazars have the most complete light curves collected during the first four years of the Fermi sky survey. We model them with the Ornstein-Uhlenbeck (OU) process or a mixture of the OU processes. The OU process has power spectral density (PSD) proportional to 1/f {sup α} with α changing at a characteristic timescale, τ{sub 0}, from 0 (τ >> τ{sub 0}) to 2 (τ << τ{sub 0}). The PSD of the mixed OU process has two characteristic timescales and an additional intermediate region with 0 < α < 2. We show that the OU model provides a good description of the Fermi/LAT light curves of three blazars in our sample. For the first time, we constrain a characteristic γ-ray timescale of variability in two BL Lac sources, 3C 66A and PKS 2155-304 (τ{sub 0} ≅ 25 days and τ{sub 0} ≅ 43 days, respectively, in the observer's frame), which are longer than the soft X-ray timescales detected in blazars and Seyfert galaxies. We find that the mixed OU process approximates the light curves of the remaining 10 blazars better than the OU process. We derive limits on their long and short characteristic timescales, and infer that their Fermi/LAT PSD resemble power-law functions. We constrain the PSD slopes for all but one source in the sample. We find hints for sub-hour Fermi/LAT variability in four flat spectrum radio quasars. We discuss the implications of our results for theoretical models of blazar variability.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2014

Natural CMT2 Variation Is Associated With Genome-Wide Methylation Changes and Temperature Seasonality

As Arabidopsis thaliana has colonized a wide range of habitats across the world it is an attractive model for studying the genetic mechanisms underlying environmental adaptation. Here, we used public data from two collections of A. thaliana accessions to associate genetic variability at individual loci with differences in climates at the sampling sites. We use a novel method to screen the genome for plastic alleles that tolerate a broader climate range than the major allele. This approach reduces confounding with population structure and increases power compared to standard genome-wide association methods. Sixteen novel loci were found, including an association between Chromomethylase 2 (CMT2) and temperature seasonality where the genome-wide CHH methylation was different for the group of accessions carrying the plastic allele. Cmt2 mutants were shown to be more tolerant to heat-stress, suggesting genetic regulation of epigenetic modifications as a likely mechanism underlying natural adaptation to variable temperatures, potentially through differential allelic plasticity to temperature-stress.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2017

Methods of Reverberation Mapping. I. Time-lag Determination by Measures of Randomness

A class of methods for measuring time delays between astronomical time series is introduced in the context of quasar reverberation mapping, which is based on measures of randomness or complexity of the data. Several distinct statistical estimators are considered that do not rely on polynomial interpolations of the light curves nor on their stochastic modeling, and do not require binning in correlation space. Methods based on von Neumann’s mean-square successive-difference estimator are found to be superior to those using other estimators. An optimized von Neumann scheme is formulated, which better handles sparsely sampled data and outperforms current implementations of discrete correlation function methods. This scheme is applied to existing reverberation data of varying quality, and consistency with previously reported time delays is found. In particular, the size–luminosity relation of the broad-line region in quasars is recovered with a scatter comparable to that obtained by other works, yet with fewer assumptions made concerning the process underlying the variability. The proposed method for time-lag determination is particularly relevant for irregularly sampled time series, and in cases where the process underlying the variability cannot be adequately modeled.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

A Molecular View of Methane Activation on Ni(111) through Enhanced Sampling and Machine Learning

A combination of machine learned interatomic potentials (MLIPs) and enhanced sampling simulations is used to investigate the activation of methane on a Ni(111) surface. The work entails the development and iterative refinement of MLIPs, initially trained on a dataset constructed via ab initio molecular dynamics (AIMD) simulations, supplemented by adaptive biasing forces, to enrich the sampling of catalytically relevant configurations. Our results reveal that by incorporating collective variables that capture the behavior of the reactant molecule, as well as additional frames that describe the dynamic response of the catalytic surface, it is possible to enhance considerably the accuracy of predicted energies and forces. By employing enhanced sampling schemes in the refinement of the MLIP, we systematically explore the potential energy surface, leading to a refined MLIP capable of predicting DFT-level energies and forces and replicating key geometric characteristics of the catalytic system. The resulting free energy landscapes at several temperatures provide a detailed view of the thermodynamics and dynamics of methane activation. Specifically, as methane approaches and dissociates on the catalytic surface, the process involves the dynamic interplay of CH 4 and the Ni catalyst that includes both enthalpic and entropic contributions. The progression towards the transition state involves an CH 4 moiety that is increasingly restrained in its ability to rotate or translate, while the stage following the transition state is characterized by a notable rise of the Ni atom that interacts with the cleaved C–H bond. Furthermore, this leads to an increase in the mobility of the adsorbed species, a feature that becomes more pronounced at higher temperatures.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Methane emission hotspots in a boreal forest-fen mosaic potentially linked to deep taliks

Permafrost thaw is transforming boreal forests into mosaics of wetlands and drier uplands. Topographic controls on hydrological and ecological conditions impact methane (CH 4 ) fluxes, contributing to uncertainty in local and regional CH 4 budgets and underlying drivers. The objective of this study was to explore CH 4 fluxes and their drivers in a transitioning boreal forest-fen ecosystem (Goldstream Valley, Alaska, USA). This landscape is characterized by thawing discontinuous permafrost and heterogeneous mosaics of fens, collapse-scar channels, and small mounds of permafrost soils. From a survey in July 2021, observed chamber CH4 fluxes included fen areas with intermediate to very high emissions (29.8–635.3 mg CH 4 m −2 d −1 ), clustered locations with CH 4 uptake (−2.11 to −0.7 mg CH 4 m −2 d −1 ), and three anomalous emission hotspots (342.4–772.4 mg CH 4 m −2 d −1 ) that were located near samples with lower emissions. Some surface and near-surface variables partially explained the spatial variation in CH 4 flux. Log-transformed CH 4 flux had a positive linear relationship with soil moisture at 20 cm depth ( R 2 = 0.31, p -value < 1e-5) and negative linear relationships with microtopography ( R 2 = 0.13, p -value < 0.006) and slope ( R 2 = 0.28, p -value < 2e-5). Methane emissions generally occurred in flat, wet, graminoid-dominated fens, whereas CH 4 uptake occurred on permafrost mounds dominated by feather mosses and woody vegetation. However, the CH 4 hotspots occurred on drier, slightly sloped locations with low or undetectable near-surface methanogen abundance, suggesting that CH 4 was produced in deeper soils. When the hotspot samples were omitted, log-transformed CH 4 flux had a positive linear relationship with near-surface methanogen abundance ( R 2 = 0.29, p -value = 0.0023), and stronger linear relationships with soil moisture, slope, and soil macronutrient concentrations. Our findings suggest that some CH 4 emission hotspots could arise from CH 4 in deep taliks. The inference that methanogenesis occurs in deep taliks was strengthened by the identification of intrapermafrost taliks across the study area using low-frequency geophysical induction. This study assesses surface spatial heterogeneity in the context of subsurface permafrost conditions and highlights the complexity of CH 4 flux patterns in transitioning forest-wetland ecosystems. To better inform regional CH 4 budgets, further research is needed to understand the spatial distribution of terrestrial CH 4 hotspots and to resolve their surface, near-surface, and subsurface drivers.

boreal↗